/*
 *    This program is free software; you can redistribute it and/or modify
 *    it under the terms of the GNU General Public License as published by
 *    the Free Software Foundation; either version 2 of the License, or
 *    (at your option) any later version.
 *
 *    This program is distributed in the hope that it will be useful,
 *    but WITHOUT ANY WARRANTY; without even the implied warranty of
 *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *    GNU General Public License for more details.
 *
 *    You should have received a copy of the GNU General Public License
 *    along with this program; if not, write to the Free Software
 *    Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
 */

/*
 * ClassificationGenerator.java
 * Copyright (C) 2000 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.datagenerators;

import weka.core.Option;
import weka.core.Utils;

import java.util.Enumeration;
import java.util.Vector;

/**
 * Abstract class for data generators for classifiers.
 * <p/>
 * 
 * @author Gabi Schmidberger (gabi@cs.waikato.ac.nz)
 * @author FracPete (fracpete at waikato dot ac dot nz)
 * @version $Revision: 1.4 $
 */
public abstract class ClassificationGenerator extends DataGenerator {

	/** for serialization */
	private static final long serialVersionUID = -5261662546673517844L;

	/** Number of instances */
	protected int m_NumExamples;

	/**
	 * initializes with default values
	 */
	public ClassificationGenerator() {
		super();

		setNumExamples(defaultNumExamples());
	}

	/**
	 * Returns an enumeration describing the available options.
	 * 
	 * @return an enumeration of all the available options.
	 */
	public Enumeration listOptions() {
		Vector result = enumToVector(super.listOptions());

		result.addElement(new Option(
				"\tThe number of examples to generate (default "
						+ defaultNumExamples() + ")", "n", 1, "-n <num>"));

		return result.elements();
	}

	/**
	 * Sets the options.
	 * 
	 * @param options
	 *            the options
	 * @throws Exception
	 *             if invalid option
	 */
	public void setOptions(String[] options) throws Exception {
		String tmpStr;

		super.setOptions(options);

		tmpStr = Utils.getOption('n', options);
		if (tmpStr.length() != 0)
			setNumExamples(Integer.parseInt(tmpStr));
		else
			setNumExamples(defaultNumExamples());
	}

	/**
	 * Gets the current settings of the classifier.
	 * 
	 * @return an array of strings suitable for passing to setOptions
	 */
	public String[] getOptions() {
		Vector result;
		String[] options;
		int i;

		result = new Vector();
		options = super.getOptions();
		for (i = 0; i < options.length; i++)
			result.add(options[i]);

		result.add("-n");
		result.add("" + getNumExamples());

		return (String[]) result.toArray(new String[result.size()]);
	}

	/**
	 * returns the default number of examples
	 * 
	 * @return the default number of examples
	 */
	protected int defaultNumExamples() {
		return 100;
	}

	/**
	 * Sets the number of examples, given by option.
	 * 
	 * @param numExamples
	 *            the new number of examples
	 */
	public void setNumExamples(int numExamples) {
		m_NumExamples = numExamples;
	}

	/**
	 * Gets the number of examples, given by option.
	 * 
	 * @return the number of examples, given by option
	 */
	public int getNumExamples() {
		return m_NumExamples;
	}

	/**
	 * Returns the tip text for this property
	 * 
	 * @return tip text for this property suitable for displaying in the
	 *         explorer/experimenter gui
	 */
	public String numExamplesTipText() {
		return "The number of examples to generate.";
	}
}
